Visualizing convolutional neural networks

Check out the full program at the TensorFlow World Conference, October 28-31, 2019. Best price ends August 2. Attention readers: We invite you to access the corresponding Python code and iPython notebooks for this article on GitHub. Given all of the higher level tools that you can use with TensorFlow, such as tf.contrib.learn But often with these higher level applications, you cannot access the little inbetween bits of the code, and some of the understanding of what's happening under the surface is lost. In this tutorial, I'll walk you through how to build a convolutional neural network from scratch, using just the low-level TensorFlow and visualizing our graph and network performance using TensorBoard. If you don't understand some of the basics of a fully connected neural network, I highly recommend you first check out Not another MNIST tutorial with TensorFlow.